All Issue

2022 Vol.9, Issue 1 Preview Page

Original Article

31 March 2022. pp. 24-35
Abstract
References
1
Chang, F.J., Tsai, Y.H., Chen, P.A., Coynel, A., and Vachaud, G. 2015. Modeling water quality in an urban river using hydrological factors-Data driven approaches. Journal of environmental management 151: 87-96. 10.1016/j.jenvman.2014.12.01425544251
2
Donigian, A.S. 2000. HSPF Training Workshop Handbook and CD, Lecture #19, Calibration and Verification Issues, Slide #L19-22, EPA Heaarters, Washington Information Center, Presented and prepared for U.S. EPA, Office of Water, Office of Science and Technology.
3
Faruk, D.Ö. 2010. A hybrid neural network and ARIMA model for water quality time series prediction. Engineering applications of artificial intelligence 23(4): 586-594. 10.1016/j.engappai.2009.09.015
4
Keum, H.J., Kim, H.I., and Kim, B. 2019. Uncertainty analysis of rainfall scenarios for the prediction of flood disasters in urban areas. Journal of the Korean Society of Hazard Mitigation 19(2): 255-264. (in Korean) 10.9798/KOSHAM.2019.19.2.255
5
Khadr, M. and Elshemy, M. 2017. Data-driven modeling for water quality prediction case study: The drains system associated with Manzala Lake, Egypt. Ain Shams Engineering Journal 8(4): 549-557. 10.1016/j.asej.2016.08.004
6
Kim, J.K., Lee, S.H., Bang, H.H., and Hwang, S.O. 2009. Characteristics of algae occurrence in Lake Paldang. Journal of Korean Society of Environmental Engineers 31(5): 325-331. (in Korean)
7
Kim, S.E. and Seo, I.W. 2015. Artificial neural network ensemble modeling with exploratory factor analysis for streamflow forecasting. Journal of Hydroinformatics 17(4): 614-639. 10.2166/hydro.2015.033
8
Kim, Y.S. and Lee, E.J. 2019. Establishment of Target Water Quality for TOC of Total Water Load Management System. Journal of Korean Society on Water Environment 35(6): 520-538. (in Korean)
9
Lee, E. and Kim, T. 2021. Predicting BOD under Various Hydrological Conditions in the Dongjin River Basin Using Physics-Based and Data-Driven Models. Water 13(10): 1383. 10.3390/w13101383
10
Lee, E.J. 2013. Application of total water load management system using watershed model and load duration curves. Doctor's thesis, Cheongju University, Choengju, Korea. (in Korean)
11
Lee, E.J., Kim, T.G., and Keum, H.J. 2018. Application of FDC and LDC using HSPF model to support total water load management system. Journal of Korean Society on Water Environment 34(1): 33-45. (in Korean)
12
Ministry Of Environment (MOE). 2015. Nam River Water Management Big Data Analysis to Prepare Water Quality Improvement Plan. (in Korean)
13
Najah, A., El-Shafie, A., Karim, O.A., and El-Shafie, A.H. 2013. Application of artificial neural networks for water quality prediction. Neural Computing and Applications 22(1): 187-201. 10.1007/s00521-012-0940-3
14
National Disaster Management Research Institute (NDMI), 2018, Developing an Analytic Framework for Real-time Inundated Hazard Area. (in Korean)
15
Niknia, N., Moghaddam, H.K., Banaei, S.M., Podeh, H.T., Omidinasab, F., and Yazdi, A.A. 2014. Application of gamma test and neuro-fuzzy models in uncertainty analysis for prediction of pipeline scouring depth. Journal of Water Resource and Protection 6(05): 514. 10.4236/jwarp.2014.65050
16
Oh, C.S. 2016. Notes on applying the EFDC model for simulating the water quality of Saemangeum watershed. Korean National Committee on Irrigation and Drainage 55: 42-48. (in Korean)
17
Park, J.D. and Oh, S.Y. 2012. Methodology for the identification of impaired waters using LDC for the management of total maximum daily loads. Journal of Korean Society on Water Environment 28(5): 693-703. (in Korean)
18
Poul, S., Manguerra, H., and Slawecki, T. 2019. A Watershed Management Perspective, Digest of water industry and business of Korean society on water environment. Big Data Anal 20-23.
19
Rauf, A., Ahmed, S., Ghumman, A.R., Ahmad, I., Khan, K.A., and Ahsan, M. 2016. Data Driven Modelling for Real-time Flood Forecasting. In Proceedings of the 2nd International Multi-Disciplinary Conference, Gujrat, Pakistan 19-20.
20
Sarkar, A. and Pandey, P. 2015. River water quality modelling using artificial neural network technique. Aquatic procedia, 4: 1070-1077. 10.1016/j.aqpro.2015.02.135
21
Seo, I.W. and Choi, N.J. 2007. Water Quality Modeling and Water Quality Forecasting. Environmental Engineering Research 55(1): 57-84. (in Korean)
22
Stefánsson, A., Končar, N., and Jones, A.J. 1997. A note on the gamma test. Neural Computing & Applications 5(3): 131-133. 10.1007/BF01413858
23
Tetra Tech, Inc. 2007. The Environmental Fluid Dynamics Code User Manual US EPA Version 1.01.
24
U.S.EPA. 2001. HSPF User's Manual.
Information
  • Publisher :Korean Society of Ecology and Infrastructure Engineering
  • Publisher(Ko) :응용생태공학회
  • Journal Title :Ecology and Resilient Infrastructure
  • Journal Title(Ko) :응용생태공학회 논문집
  • Volume : 9
  • No :1
  • Pages :24-35
  • Received Date : 2022-01-22
  • Revised Date : 2022-02-08
  • Accepted Date : 2022-02-11